PSC Beam교 환경부하량 추정을 위한 인공신경망 모델 적용 연구

Application of Artificial Neural Network Model for Environmental Load Estimation of Pre-Stressed Concrete Beam Bridge

초록

Considering that earlier stage of construction project has a great influence on the possibility of lowering of environmental load, it is important to build and utilize system that can support effective decision making at the initial stage of the project. In this study, we constructed an environmental load estimation model that can be used at the early stage of the project using basic design factors. The model was constructed by using the artificial neural network to estimate environmental load by applying to planning stage (ANN-1), basic design stage (ANN-2). The result of test, shows that average of absolute measuring efficiency and standard deviation of ANN-1 and ANN-2 were 11.19% / 5.30% and 9.59% / 3.09% each. This result indicates that the model using the input variables extended with the project progress has high reliability and it is considered to be effective in decision support at the initial design stage of the project.

키워드

환경부하전과정평가PSC 빔교인공신경망Environmental LoadLife Cycle AssessmentPSC BeamArtificial Neural Network
제목
PSC Beam교 환경부하량 추정을 위한 인공신경망 모델 적용 연구
제목 (타언어)
Application of Artificial Neural Network Model for Environmental Load Estimation of Pre-Stressed Concrete Beam Bridge
저자
김의왕윤원건김경주
DOI
10.6106/KJCEM.2018.19.4.082
발행일
2018-07
저널명
한국건설관리학회 논문집
19
4
페이지
82 ~ 92